Smruti612/Llama-2-7b-chat-finetune_revise_smart

mlabonne/guanaco-llama2-1k language: en base_model: NousResearch/Llama-2-7b-chat-hf pipeline_tag: text-generation tags: llama causal-lm text-generation fine-tuned

Fine-tuned LLaMA Model This repository contains a fine-tuned version of the LLaMA model, optimized for enhanced text generation capabilities. Model Description

Model Architecture: LLaMA (Large Language Model Meta AI) Base Model: NousResearch/Llama-2-7b-chat-hf Training Type: Fine-tuning Language(s): English License: MIT

Intended Uses This model is designed for:

Text generation Conversation completion Natural language understanding tasks

Training and Evaluation The model was fine-tuned on mlabonne/guanaco-llama2-1k dataset.

from transformers import AutoTokenizer, AutoModelForCausalLM

Load model and tokenizer

tokenizer = AutoTokenizer.from_pretrained("Smruti612/Llama-2-7b-chat-finetune_revise_smart") model = AutoModelForCausalLM.from_pretrained("Smruti612/Llama-2-7b-chat-finetune_revise_smart")

Example usage

text = "Your input text here" inputs = tokenizer(text, return_tensors="pt") outputs = model.generate(**inputs, max_length=100) result = tokenizer.decode(outputs[0], skip_special_tokens=True) print(result)

Model Details

Base Model: Llama-2-7b-chat-hf Training Dataset: guanaco-llama2-1k

@misc{Smruti612/Llama-2-7b-chat-finetune_revise_smart, author = {Smruti Sonekar}, title = {Fine-tuned LLaMA Model}, year = {2024}, publisher = {Hugging Face}, journal = {Hugging Face Model Hub}, }

Limitations

Model outputs may occasionally be inaccurate or contain biases Performance may vary depending on the specific use case Limited by context window size

Acknowledgments This model builds upon the LLaMA architecture developed by Meta AI. We acknowledge their contribution to the field of large language models.